An interactive fuzzy satisficing method based on variance minimization under expectation constraints for multiobjective stochastic linear programming problems
An interactive fuzzy satisficing method based on variance minimization under expectation constraints for multiobjective stochastic linear programming problems
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DOI：
10.1007/s00500-010-0540-z
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发表时间：
2011
期刊：
影响因子：
4.1
通讯作者：
Kosuke Kato;M. Sakawa
中科院分区：
文献类型：
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作者：
Kosuke Kato;M. Sakawa
在本文中，我们重点研究涉及目标函数和约束中的随机变量系数的多目标线性规划问题。利用机会约束条件的概念，基于期望约束下的方差最小化模型，将此类多目标随机线性规划问题转化为确定性问题。在引入模糊目标来反映决策者对目标函数判断的模糊性之后，我们提出了一种交互式模糊满足方法，作为随机规划和模糊规划的融合，为它们导出满意的解决方案。将所提出的方法应用于说明性数值示例表明了其有用性。
In this paper, we focus on multiobjective linear programming problems involving random variable coefficients in objective functions and constraints. Using the concept of chance constrained conditions, such multiobjective stochastic linear programming problems are transformed into deterministic ones based on the variance minimization model under expectation constraints. After introducing fuzzy goals to reflect the ambiguity of the decision maker’s judgements for objective functions, we propose an interactive fuzzy satisficing method to derive a satisficing solution for them as a fusion of the stochastic programming and the fuzzy one. The application of the proposed method to an illustrative numerical example shows its usefulness.